Autism
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Most Cited JCPP Articles #55 of 60
Most cited JCPP papers #55 of 60: Annotation: What do we know about sensory dysfunction in autism? A critical review of the empirical evidence
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Most Cited JCPP Articles #56 of 60
Most cited JCPP papers #56 of 60: “SOCIAL INTERACTIONS OF AUTISTIC, MENTALLY-RETARDED AND NORMAL-CHILDREN AND THEIR CAREGIVERS”
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Most Cited JCPP Articles #58 of 60
Most cited JCPP papers #58 of 60: Autism spectrum disorders at 20 and 42 months of age: Stability of clinical and ADI-R diagnosis
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Most Cited JCPP Articles #60 of 60
Most cited JCPP papers #60 of 60: Outcome at 7 years of children diagnosed with autism at age 2: predictive validity of assessments conducted at 2 and 3 years of age and pattern of symptom change over time.
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JCPP Editorial: Volume 59, Issue 11, November 2018
“Autistic social behaviors and the half‐empty, half‐full cup” by Charles H. Zeanah
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The importance of identifying an Intellectual Disability/Learning Disability for the individual, parents/carers and from a service/policy perspective
The importance of identifying an Intellectual Disability/Learning Disability for the individual, parents/carers and from a service/policy perspective.
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Autism and Attachment: A Need for Conceptual Clarity
What do we mean by ‘attachment disorders’? Is there a meaningful distinction between these disorders and ‘attachment difficulties’? And where is the overlap with autism?
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Children with ASD show intact statistical word learning
Children with autism spectrum disorder (ASD) and specific language impairment (SLI) exhibit word-learning difficulties early in childhood development.
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Machine learning improves ADI-R efficiency
Early interventions in autism spectrum disorder (ASD) are essential to improve communication and behavioural skills in affected children. Now, researchers have used machine learning to derive new instrument algorithms that may help practitioners screen for autism more efficiently and effectively.
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Can this app help autistic people with anxiety?
Available on the Apple App Store today, Molehill Mountain is the first evidence-led smartphone app aiming to help autistic adults understand and self-manage their own anxiety. The app has been developed by UK research charity Autistica and researchers at King’s College London with input from autistic people.
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